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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "mtrank" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'mtrank: Ranking using Probabilistic Models and Treatment Choice Criteria'
version: 0.1-1
doi: 10.32614/CRAN.package.mtrank
abstract: Implementation of a novel frequentist approach to produce clinically relevant
  treatment hierarchies in network meta-analysis. The method is based on treatment
  choice criteria (TCC) and probabilistic ranking models, as described by Evrenoglou
  et al. (2024) <DOI:10.48550/arXiv.2406.10612>. The TCC are defined using a rule
  based on the minimal clinically important difference. Using the defined TCC, the
  study-level data (i.e., treatment effects and standard errors) are first transformed
  into a preference format, indicating either a treatment preference (e.g., treatment
  A > treatment B) or a tie (treatment A = treatment B). The preference data are then
  synthesized using a probabilistic ranking model, which estimates the latent ability
  parameter of each treatment and produces the final treatment hierarchy. This parameter
  represents each treatment’s ability to outperform all the other competing treatments
  in the network. Consequently, larger ability estimates indicate higher positions
  in the ranking list.
authors:
- family-names: Evrenoglou
  given-names: Theodoros
  email: theodoros.evrenoglou@uniklinik-freiburg.de
  orcid: https://orcid.org/0000-0003-3336-8058
- family-names: Schwarzer
  given-names: Guido
  orcid: https://orcid.org/0000-0001-6214-9087
repository: https://tevrenoglou.r-universe.dev
repository-code: https://github.com/TEvrenoglou/mtrank
commit: 0042ee9678586c24b95a66d2e8451c435adbf9a8
url: https://github.com/TEvrenoglou/mtrank
date-released: '2025-02-26'
contact:
- family-names: Evrenoglou
  given-names: Theodoros
  email: theodoros.evrenoglou@uniklinik-freiburg.de
  orcid: https://orcid.org/0000-0003-3336-8058